Dear all, I am using mixtools' normalmixEM to find a cut-off that can separate two populations. I can run the model, but I have two problems: 1. how do I find the value that separates the two populations? The model provides two density plots, what would be the value that is at the intersection between the two distribution and that constitutes the best cut-off? 2. is it possible to reproduce the plots given by normalmixEM using basic R functions?
Here is an example: >>> pos = rnorm(100, mean = 1, sd = 1) neg = rnorm(100, mean = 0, sd = 3) X = c(pos, neg) dX = density(X) dp = density(pos) dn = density(neg) plot(dX) points(dp, type = "l", col = "green") points(dn, type = "l", col = "red") library(mixtools) model = normalmixEM((x = X)) print(summary(model)) muneg = model$mu[1] # Mean of negative population sdneg = model$sigma[1] # SD of negative population mupos = model$mu[2] # Mean of positive population sdpos = model$sigma[2] # SD of positive population plot(model, which=2) abline(v=0.058, lty = 2, col = "blue", lwd = 2) <<< the first plot shows that the two populations (pos and neg) are distinct since their mean values are shifted one another. The second plot reproduces this distinction and the intersection point between the red (neg) and green (pos) distributions should be the cut-off between the populations. in this case, I find it manually at 0.058 (blue line). How can I calculate it properly? Thank you. -- Best regards, Luigi ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
